Evidence map›Paper›PMID 42211502›Full record

ArticleFrontiers in oncology2026

MRI-based habitat radiomics for preoperative prediction of axillary pathological complete response in breast cancer after neoadjuvant therapy: a multicenter study.

Lei Ma, Shunian Li, Ziwei Cao, Jun Liao, Mengting Xu, Chuanjian Lv, Chunmiao Xu, Hongna Tan

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Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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8 authors.

Lei Ma *Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China.
Shunian Li *Department of Radiology, People's Hospital of Zhengzhou University & Henan Provincial People's Hospital, Zhengzhou, China.
Ziwei Cao *Department of Radiology, People's Hospital of Zhengzhou University & Henan Provincial People's Hospital, Zhengzhou, China.
Jun LiaoDepartment of Radiology, People's Hospital of Zhengzhou University & Henan Provincial People's Hospital, Zhengzhou, China.
Mengting XuDepartment of Radiology, People's Hospital of Henan University & Henan Provincial People's Hospital, Zhengzhou, China.
Chuanjian LvDepartment of Radiology, Henan Provincial People's Hospital, Zhengzhou, China.
Chunmiao XuDepartment of Medical Imaging, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
Hongna TanDepartment of Radiology, Henan Provincial People's Hospital, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To develop and validate a preoperative MRI-based habitat radiomics nomogram for noninvasive prediction of axillary pathological complete response (apCR) after neoadjuvant therapy (NAT) in node-positive breast cancer. Patients and methods: This retrospective multicenter study included patients with histologically confirmed node-positive breast cancer from two institutions who underwent pretreatment breast MRI. Dynamic contrast-enhanced MRI was used for tumor segmentation and to define intratumoral habitat subregions based on enhancement heterogeneity. Radiomic features were extracted from whole tumors and habitat subregions, and radiomics and habitat signatures were integrated with clinicopathologic variables to construct a nomogram for preoperative prediction of apCR. Model performance was evaluated using receiver operating characteristic (ROC) analysis, calibration assessment, and decision curve analysis (DCA). Results: A total of 336 women were included. In the training cohort, the radiomics, habitat, and nomogram models achieved AUCs of 0.723, 0.765, and 0.845, respectively. The nomogram consistently demonstrated the highest discriminative performance in the internal validation and independent external test cohorts, with AUCs of 0.755 and 0.754. Calibration analysis showed good agreement between predicted and observed apCR, and DCA indicated greater net clinical benefit for the nomogram. Conclusion: The proposed MRI-based habitat radiomics nomogram showed promising performance for noninvasive, preoperative prediction of apCR after NAT and may assist individualized axillary risk stratification in patients with node-positive breast cancer.

Indexed as

axillary pathological complete responsebreast cancerhabitat radiomicsmagnetic resonance imagingneoadjuvant therapy

Identifiers

PMID42211502
PMCPMC13212183

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